update qlora
Browse files- README.md +418 -2
- adapter_config.json +9 -2
- adapter_model.bin +2 -2
- training_log.json +0 -16
- training_parameters.json +19 -12
- training_prompt.json +3 -1
README.md
CHANGED
@@ -1,10 +1,342 @@
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---
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library_name: peft
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---
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- load_in_8bit: True
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- load_in_4bit: False
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- llm_int8_threshold: 6.0
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- bnb_4bit_use_double_quant: False
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- bnb_4bit_compute_dtype: float32
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The following `bitsandbytes` quantization config was used during training:
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- load_in_8bit: True
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- load_in_4bit: False
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- llm_int8_threshold: 6.0
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- bnb_4bit_quant_type: fp4
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- bnb_4bit_use_double_quant: False
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- bnb_4bit_compute_dtype: float32
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### Framework versions
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- PEFT 0.5.0.dev0
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-
- PEFT 0.
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---
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library_name: peft
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base_model: models\LLaMA2-13B-Tiefighter
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- quant_method: QuantizationMethod.BITS_AND_BYTES
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- load_in_8bit: False
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- load_in_4bit: True
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- llm_int8_threshold: 6.0
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- llm_int8_skip_modules: None
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- llm_int8_enable_fp32_cpu_offload: False
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- llm_int8_has_fp16_weight: False
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- bnb_4bit_quant_type: nf4
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- bnb_4bit_use_double_quant: False
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- bnb_4bit_compute_dtype: float16
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### Framework versions
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- PEFT 0.6.2
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- quant_method: QuantizationMethod.BITS_AND_BYTES
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- load_in_8bit: False
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- load_in_4bit: True
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- llm_int8_threshold: 6.0
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- llm_int8_skip_modules: None
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- llm_int8_enable_fp32_cpu_offload: False
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- llm_int8_has_fp16_weight: False
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- bnb_4bit_quant_type: nf4
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- bnb_4bit_use_double_quant: False
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- bnb_4bit_compute_dtype: float16
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### Framework versions
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- PEFT 0.6.2
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- quant_method: QuantizationMethod.BITS_AND_BYTES
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- load_in_8bit: False
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- load_in_4bit: True
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- llm_int8_threshold: 6.0
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- llm_int8_skip_modules: None
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- llm_int8_enable_fp32_cpu_offload: False
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- llm_int8_has_fp16_weight: False
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- bnb_4bit_quant_type: nf4
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- bnb_4bit_use_double_quant: False
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- bnb_4bit_compute_dtype: float16
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### Framework versions
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- PEFT 0.6.2
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- quant_method: QuantizationMethod.BITS_AND_BYTES
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- load_in_8bit: False
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- load_in_4bit: True
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- llm_int8_threshold: 6.0
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- llm_int8_skip_modules: None
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- llm_int8_enable_fp32_cpu_offload: False
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- llm_int8_has_fp16_weight: False
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- bnb_4bit_quant_type: nf4
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- bnb_4bit_use_double_quant: False
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- bnb_4bit_compute_dtype: float16
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### Framework versions
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- PEFT 0.6.2
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- quant_method: QuantizationMethod.BITS_AND_BYTES
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- load_in_8bit: False
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- load_in_4bit: True
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- llm_int8_threshold: 6.0
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- llm_int8_skip_modules: None
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- llm_int8_enable_fp32_cpu_offload: False
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- llm_int8_has_fp16_weight: False
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- bnb_4bit_quant_type: nf4
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- bnb_4bit_use_double_quant: False
|
291 |
+
- bnb_4bit_compute_dtype: float16
|
292 |
+
|
293 |
+
### Framework versions
|
294 |
+
|
295 |
+
|
296 |
+
- PEFT 0.6.2
|
297 |
+
## Training procedure
|
298 |
+
|
299 |
+
|
300 |
+
The following `bitsandbytes` quantization config was used during training:
|
301 |
+
- quant_method: QuantizationMethod.BITS_AND_BYTES
|
302 |
+
- load_in_8bit: False
|
303 |
+
- load_in_4bit: True
|
304 |
+
- llm_int8_threshold: 6.0
|
305 |
+
- llm_int8_skip_modules: None
|
306 |
+
- llm_int8_enable_fp32_cpu_offload: False
|
307 |
+
- llm_int8_has_fp16_weight: False
|
308 |
+
- bnb_4bit_quant_type: nf4
|
309 |
+
- bnb_4bit_use_double_quant: False
|
310 |
+
- bnb_4bit_compute_dtype: float16
|
311 |
+
|
312 |
+
### Framework versions
|
313 |
+
|
314 |
+
|
315 |
+
- PEFT 0.6.2
|
316 |
+
## Training procedure
|
317 |
+
|
318 |
+
|
319 |
+
The following `bitsandbytes` quantization config was used during training:
|
320 |
+
- quant_method: QuantizationMethod.BITS_AND_BYTES
|
321 |
+
- load_in_8bit: True
|
322 |
+
- load_in_4bit: False
|
323 |
+
- llm_int8_threshold: 6.0
|
324 |
+
- llm_int8_skip_modules: None
|
325 |
+
- llm_int8_enable_fp32_cpu_offload: True
|
326 |
+
- llm_int8_has_fp16_weight: False
|
327 |
+
- bnb_4bit_quant_type: fp4
|
328 |
+
- bnb_4bit_use_double_quant: False
|
329 |
+
- bnb_4bit_compute_dtype: float32
|
330 |
+
|
331 |
+
### Framework versions
|
332 |
+
|
333 |
+
|
334 |
+
- PEFT 0.6.2
|
335 |
+
## Training procedure
|
336 |
+
|
337 |
+
|
338 |
+
The following `bitsandbytes` quantization config was used during training:
|
339 |
+
- quant_method: QuantizationMethod.BITS_AND_BYTES
|
340 |
- load_in_8bit: True
|
341 |
- load_in_4bit: False
|
342 |
- llm_int8_threshold: 6.0
|
|
|
347 |
- bnb_4bit_use_double_quant: False
|
348 |
- bnb_4bit_compute_dtype: float32
|
349 |
|
350 |
+
### Framework versions
|
351 |
+
|
352 |
+
|
353 |
+
- PEFT 0.6.2
|
354 |
+
## Training procedure
|
355 |
+
|
356 |
+
|
357 |
The following `bitsandbytes` quantization config was used during training:
|
358 |
+
- quant_method: QuantizationMethod.BITS_AND_BYTES
|
359 |
- load_in_8bit: True
|
360 |
- load_in_4bit: False
|
361 |
- llm_int8_threshold: 6.0
|
|
|
365 |
- bnb_4bit_quant_type: fp4
|
366 |
- bnb_4bit_use_double_quant: False
|
367 |
- bnb_4bit_compute_dtype: float32
|
368 |
+
|
369 |
+
### Framework versions
|
370 |
+
|
371 |
+
|
372 |
+
- PEFT 0.6.2
|
373 |
+
## Training procedure
|
374 |
+
|
375 |
+
|
376 |
+
The following `bitsandbytes` quantization config was used during training:
|
377 |
+
- quant_method: QuantizationMethod.BITS_AND_BYTES
|
378 |
+
- load_in_8bit: False
|
379 |
+
- load_in_4bit: True
|
380 |
+
- llm_int8_threshold: 6.0
|
381 |
+
- llm_int8_skip_modules: None
|
382 |
+
- llm_int8_enable_fp32_cpu_offload: False
|
383 |
+
- llm_int8_has_fp16_weight: False
|
384 |
+
- bnb_4bit_quant_type: nf4
|
385 |
+
- bnb_4bit_use_double_quant: False
|
386 |
+
- bnb_4bit_compute_dtype: float16
|
387 |
+
|
388 |
+
### Framework versions
|
389 |
+
|
390 |
+
|
391 |
+
- PEFT 0.6.2
|
392 |
+
## Training procedure
|
393 |
+
|
394 |
+
|
395 |
+
The following `bitsandbytes` quantization config was used during training:
|
396 |
+
- quant_method: QuantizationMethod.BITS_AND_BYTES
|
397 |
+
- load_in_8bit: False
|
398 |
+
- load_in_4bit: True
|
399 |
+
- llm_int8_threshold: 6.0
|
400 |
+
- llm_int8_skip_modules: None
|
401 |
+
- llm_int8_enable_fp32_cpu_offload: False
|
402 |
+
- llm_int8_has_fp16_weight: False
|
403 |
+
- bnb_4bit_quant_type: nf4
|
404 |
+
- bnb_4bit_use_double_quant: False
|
405 |
+
- bnb_4bit_compute_dtype: float16
|
406 |
+
|
407 |
+
### Framework versions
|
408 |
+
|
409 |
+
|
410 |
+
- PEFT 0.6.2
|
411 |
+
## Training procedure
|
412 |
+
|
413 |
+
|
414 |
+
The following `bitsandbytes` quantization config was used during training:
|
415 |
+
- quant_method: QuantizationMethod.BITS_AND_BYTES
|
416 |
+
- load_in_8bit: False
|
417 |
+
- load_in_4bit: True
|
418 |
+
- llm_int8_threshold: 6.0
|
419 |
+
- llm_int8_skip_modules: None
|
420 |
+
- llm_int8_enable_fp32_cpu_offload: False
|
421 |
+
- llm_int8_has_fp16_weight: False
|
422 |
+
- bnb_4bit_quant_type: nf4
|
423 |
+
- bnb_4bit_use_double_quant: False
|
424 |
+
- bnb_4bit_compute_dtype: float16
|
425 |
+
|
426 |
+
### Framework versions
|
427 |
+
|
428 |
+
|
429 |
+
- PEFT 0.6.2
|
430 |
+
## Training procedure
|
431 |
+
|
432 |
+
|
433 |
+
The following `bitsandbytes` quantization config was used during training:
|
434 |
+
- quant_method: QuantizationMethod.BITS_AND_BYTES
|
435 |
+
- load_in_8bit: False
|
436 |
+
- load_in_4bit: True
|
437 |
+
- llm_int8_threshold: 6.0
|
438 |
+
- llm_int8_skip_modules: None
|
439 |
+
- llm_int8_enable_fp32_cpu_offload: False
|
440 |
+
- llm_int8_has_fp16_weight: False
|
441 |
+
- bnb_4bit_quant_type: nf4
|
442 |
+
- bnb_4bit_use_double_quant: False
|
443 |
+
- bnb_4bit_compute_dtype: float16
|
444 |
+
|
445 |
### Framework versions
|
446 |
|
|
|
447 |
|
448 |
+
- PEFT 0.6.2
|
adapter_config.json
CHANGED
@@ -1,6 +1,7 @@
|
|
1 |
{
|
|
|
2 |
"auto_mapping": null,
|
3 |
-
"base_model_name_or_path": "models
|
4 |
"bias": "none",
|
5 |
"fan_in_fan_out": false,
|
6 |
"inference_mode": true,
|
@@ -12,10 +13,16 @@
|
|
12 |
"modules_to_save": null,
|
13 |
"peft_type": "LORA",
|
14 |
"r": 128,
|
|
|
15 |
"revision": null,
|
16 |
"target_modules": [
|
|
|
|
|
|
|
17 |
"q_proj",
|
18 |
-
"
|
|
|
|
|
19 |
],
|
20 |
"task_type": "CAUSAL_LM"
|
21 |
}
|
|
|
1 |
{
|
2 |
+
"alpha_pattern": {},
|
3 |
"auto_mapping": null,
|
4 |
+
"base_model_name_or_path": "models\\LLaMA2-13B-Tiefighter",
|
5 |
"bias": "none",
|
6 |
"fan_in_fan_out": false,
|
7 |
"inference_mode": true,
|
|
|
13 |
"modules_to_save": null,
|
14 |
"peft_type": "LORA",
|
15 |
"r": 128,
|
16 |
+
"rank_pattern": {},
|
17 |
"revision": null,
|
18 |
"target_modules": [
|
19 |
+
"gate_proj",
|
20 |
+
"o_proj",
|
21 |
+
"down_proj",
|
22 |
"q_proj",
|
23 |
+
"up_proj",
|
24 |
+
"v_proj",
|
25 |
+
"k_proj"
|
26 |
],
|
27 |
"task_type": "CAUSAL_LM"
|
28 |
}
|
adapter_model.bin
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:a28bb35807a1e0701ca619f722aba6f153335a231ca8fb59ee8c3af441f4bf98
|
3 |
+
size 2002982666
|
training_log.json
DELETED
@@ -1,16 +0,0 @@
|
|
1 |
-
{
|
2 |
-
"base_model_name": "mythalion-13b",
|
3 |
-
"base_model_class": "LlamaForCausalLM",
|
4 |
-
"base_loaded_in_4bit": false,
|
5 |
-
"base_loaded_in_8bit": true,
|
6 |
-
"projections": "q, v",
|
7 |
-
"loss": 0.9646,
|
8 |
-
"learning_rate": 0.00015,
|
9 |
-
"epoch": 1.88,
|
10 |
-
"current_steps": 46,
|
11 |
-
"train_runtime": 87.3735,
|
12 |
-
"train_samples_per_second": 2.232,
|
13 |
-
"train_steps_per_second": 0.034,
|
14 |
-
"total_flos": 2487721328640000.0,
|
15 |
-
"train_loss": 0.9646244049072266
|
16 |
-
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
training_parameters.json
CHANGED
@@ -1,30 +1,37 @@
|
|
1 |
{
|
2 |
"lora_name": "charluv-lora",
|
3 |
-
"always_override":
|
4 |
-
"save_steps":
|
5 |
"micro_batch_size": 4,
|
6 |
-
"batch_size":
|
7 |
-
"epochs":
|
8 |
"learning_rate": "3e-4",
|
9 |
-
"lr_scheduler_type": "
|
10 |
"lora_rank": 128,
|
11 |
"lora_alpha": 256,
|
12 |
"lora_dropout": 0.05,
|
13 |
"cutoff_len": 256,
|
14 |
-
"dataset": "
|
15 |
"eval_dataset": "None",
|
16 |
-
"format": "
|
17 |
"eval_steps": 100.0,
|
18 |
-
"raw_text_file": "
|
19 |
-
"overlap_len": 128,
|
20 |
-
"newline_favor_len": 128,
|
21 |
"higher_rank_limit": false,
|
22 |
"warmup_steps": 100.0,
|
23 |
"optimizer": "adamw_torch",
|
24 |
"hard_cut_string": "\\n\\n\\n",
|
25 |
"train_only_after": "",
|
26 |
-
"stop_at_loss": 1
|
27 |
"add_eos_token": false,
|
28 |
"min_chars": 0.0,
|
29 |
-
"report_to": "
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
30 |
}
|
|
|
1 |
{
|
2 |
"lora_name": "charluv-lora",
|
3 |
+
"always_override": true,
|
4 |
+
"save_steps": 1000.0,
|
5 |
"micro_batch_size": 4,
|
6 |
+
"batch_size": 0,
|
7 |
+
"epochs": 1.0,
|
8 |
"learning_rate": "3e-4",
|
9 |
+
"lr_scheduler_type": "linear",
|
10 |
"lora_rank": 128,
|
11 |
"lora_alpha": 256,
|
12 |
"lora_dropout": 0.05,
|
13 |
"cutoff_len": 256,
|
14 |
+
"dataset": "training",
|
15 |
"eval_dataset": "None",
|
16 |
+
"format": "alpaca-format",
|
17 |
"eval_steps": 100.0,
|
18 |
+
"raw_text_file": "None",
|
|
|
|
|
19 |
"higher_rank_limit": false,
|
20 |
"warmup_steps": 100.0,
|
21 |
"optimizer": "adamw_torch",
|
22 |
"hard_cut_string": "\\n\\n\\n",
|
23 |
"train_only_after": "",
|
24 |
+
"stop_at_loss": 0.1,
|
25 |
"add_eos_token": false,
|
26 |
"min_chars": 0.0,
|
27 |
+
"report_to": "None",
|
28 |
+
"precize_slicing_overlap": true,
|
29 |
+
"add_eos_token_type": "Every Block",
|
30 |
+
"save_steps_under_loss": 1.8,
|
31 |
+
"add_bos_token": true,
|
32 |
+
"training_projection": "all",
|
33 |
+
"sliding_window": false,
|
34 |
+
"warmup_ratio": 0,
|
35 |
+
"grad_accumulation": 1,
|
36 |
+
"neft_noise_alpha": 0
|
37 |
}
|
training_prompt.json
CHANGED
@@ -1,3 +1,5 @@
|
|
1 |
{
|
2 |
-
"template_type": "
|
|
|
|
|
3 |
}
|
|
|
1 |
{
|
2 |
+
"template_type": "dataset",
|
3 |
+
"template_1": "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n%instruction%\n\n### Response:\n%output%",
|
4 |
+
"template_2": "Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n### Instruction:\n%instruction%\n\n### Input:\n%input%\n\n### Response:\n%output%"
|
5 |
}
|